FKIE_CVE-2026-75513
Vulnerability from fkie_nvd - Published: 2026-09-16 21:17 - Updated: 2026-09-16 21:17
Severity
Summary
Marten is a .NET Transactional Document DB and Event Store on PostgreSQL. From version 7.0.0 until 9.13.0, several Marten LINQ and tenant-management paths interpolate runtime, potentially attacker-controlled strings into single-quoted SQL literals without escaping or parameterization. The primary confirmed vector is a dictionary indexer key used by Where filters in src/Marten/Linq/Members/Dictionaries/DictionaryItemMember.cs. Additional affected sinks include SelectParser.cs, DatabaseScopedTenantPartitions.cs, and DeleteAllForTenant.cs reached through IEventStore.DeleteProjectionProgressAsync, while DictionaryContainsKeyFilter.cs (Newtonsoft serializer only; System.Text.Json is not affected) handles ContainsKey calls. Events/Daemon/Internals/EventLoader.cs contains a related per-tenant partition-pruning literal that the advisory identifies as a defense-in-depth sink. A crafted single quote can escape the generated literal, enabling filter or multi-tenant authorization bypass and blind data exfiltration, and deployments that permit semicolon-batched Npgsql statements may also allow data modification. This issue is fixed in version 9.13.0.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "marten",
"vendor": "JasperFx",
"versions": [
{
"status": "affected",
"version": "\u003e= 7.0.0, \u003c 9.13.0"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Marten is a .NET Transactional Document DB and Event Store on PostgreSQL. From version 7.0.0 until 9.13.0, several Marten LINQ and tenant-management paths interpolate runtime, potentially attacker-controlled strings into single-quoted SQL literals without escaping or parameterization. The primary confirmed vector is a dictionary indexer key used by Where filters in src/Marten/Linq/Members/Dictionaries/DictionaryItemMember.cs. Additional affected sinks include SelectParser.cs, DatabaseScopedTenantPartitions.cs, and DeleteAllForTenant.cs reached through IEventStore.DeleteProjectionProgressAsync, while DictionaryContainsKeyFilter.cs (Newtonsoft serializer only; System.Text.Json is not affected) handles ContainsKey calls. Events/Daemon/Internals/EventLoader.cs contains a related per-tenant partition-pruning literal that the advisory identifies as a defense-in-depth sink. A crafted single quote can escape the generated literal, enabling filter or multi-tenant authorization bypass and blind data exfiltration, and deployments that permit semicolon-batched Npgsql statements may also allow data modification. This issue is fixed in version 9.13.0."
}
],
"id": "CVE-2026-75513",
"lastModified": "2026-09-16T21:17:13.563",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 9.1,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "LOW",
"privilegesRequired": "LOW",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L",
"version": "3.1"
},
"exploitabilityScore": 3.1,
"impactScore": 5.3,
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
},
"published": "2026-09-16T21:17:13.440",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/JasperFx/marten/commit/61882d0424854cb48703f08bdb246894ac576bed"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/JasperFx/marten/pull/4911"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/JasperFx/marten/releases/tag/9.13.0"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/JasperFx/marten/security/advisories/GHSA-rfx3-98h7-v3xp"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-89"
}
],
"source": "security-advisories@github.com",
"type": "Primary"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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